social media reveals psychosocial effects of the covid-19 ...€¦ · 2020-08-07 · social media...

Original PaperKoustuvSaha1*,B.Tech;JohnTorous2,M.D.;EricD.Caine3,M.D.;MunmunDeChoudhury1,Ph.D.1SchoolofInteractiveComputing,GeorgiaInstituteofTechnology,Atlanta,GA,USA2BethIsraelDeaconessMedicalCenter,DepartmentofPsychiatry,HarvardMedicalSchool,Boston,MA,USA3DepartmentofPsychiatry,UniversityofRochesterMedicalCenter,Rochester,NY,USA*koustuv.saha@gatech.edu

Social Media Reveals Psychosocial Effects of the COVID-19 Pandemic

Abstract Background:Thenovelcoronavirusdisease2019(COVID-19)pandemichascausedseveraldisruptionsinpersonalandcollectivelivesworldwide.Theuncertaintiessurroundingthepandemichavealsoledtomulti-facetedmentalhealthconcerns,whichcanbeexacerbatedwithprecautionarymeasuressuchassocialdistancingandself-quarantining,aswellassocietalimpactssuchaseconomicdownturnandjobloss.Despitenotingthisasa“mentalhealthtsunami,”thepsychologicaleffectsoftheCOVID-19crisisremainsunexploredatscale.Consequently,publichealthstakeholdersarecurrentlylimitedinidentifyingwaystoprovidetimelyandtailoredsupportduringthesecircumstances.Objective:Ourworkaimstoprovideinsightsregardingpeople’spsychosocialconcernsduringtheCOVID-19pandemicbyleveragingsocialmediadata.Weaimtostudythetemporalandlinguisticchangesinsymptomaticmentalhealthandsupport-seekingexpressionsinthepandemiccontext.Methods:Weobtain∼60MTwitterstreamingpostsoriginatingfromtheU.S.fromMarch,24–May,25,2020,andcomparethesewith∼40Mpostsfromacomparableperiodin2019tocausallyattributetheeffectofCOVID-19onpeople’ssocialmediaself-disclosure.Usingthesedatasets,westudypeople’sself-disclosureonsocialmediaintermsofsymptomaticmentalhealthconcernsandexpressionsseekingsupport.Weemploytransferlearningclassifiersthatidentifythesocialmedialanguageindicativeofmentalhealthoutcomes(anxiety,depression,stress,andsuicidalideation)andsupport(emotionalandinformationalsupport).Wethenexaminethechangesinpsychosocialexpressionsovertimeandlanguage,comparingthe2020and2019datasets.Results:WefindthatalloftheexaminedpsychosocialexpressionshavesignificantlyincreasedduringtheCOVID-19crisis–mentalhealthsymptomaticexpressionshaveincreasedby~14%,andsupportseekingexpressionshaveincreasedby~5%,boththematicallyrelatedtoCOVID-19.WealsoobserveasteadydeclineandeventualplateauingintheseexpressionsduringtheCOVID-19

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pandemic,whichmayhavebeenduetohabituationorduetosupportivepolicymeasuresenactedduringthisperiod.OurlanguageanalyseshighlightthatpeopleexpressconcernsthatarecontextuallyrelatedtotheCOVID-19crisis.Conclusions:WestudiedthepsychosocialeffectsoftheCOVID-19crisisbyusingsocialmediadatafrom2020,findingthatpeople’smentalhealthsymptomaticandsupport-seekingexpressionssignificantlyincreasedduringtheCOVID-19periodascomparedtosimilardatafrom2019.However,thiseffectgraduallylessenedovertime,suggestingthatpeopleadaptedtothecircumstancesandtheir“newnormal”.Ourlinguisticanalysesrevealedthatpeopleexpressedmentalhealthconcernsregardingpersonalandprofessionalchallenges,healthcareandprecautionarymeasures,andpandemic-relatedawareness.Thisworkshowsthepotentialtoprovideinsightstomentalhealthcareandstakeholdersandpolicymakersinplanningandimplementingmeasurestomitigatementalhealthrisksamidstthehealthcrisis.

Keywords:socialmedia;Twitter;language;psychosocialeffects;mentalhealth;transferlearning;depression;anxiety;stress;socialsupport;emotions;COVID-19;coronavirus;crisis

Introduction Theimpactsofglobalpublichealthemergenciesextendbeyondmedicalrepercussions–theyaffectindividualsandsocietiesonmanylevels,causingdisruptions[1,2].InanarticlewrittenbytheAmericanPsychologicalAssociationfollowingtheEbolaoutbreak[3],theepidemicwasdescribedasan“epidemicoffear”–intheUnitedStates,itwasdescribedbythemediaas“fearbola,”todescribeaparanoiathatinfectedthecountry.Reportsofsimilarfeelingsofanxiety,stress,anduncertaintyhavebeenrepeatedlyreportedduringotherglobaloutbreaksandpandemics[4].Theongoingoutbreakofthecoronavirus,SARS-COV-2,hasledtoapandemicofillness(coronavirusdisease,orCOVID-19)thathasgloballycaused16Mcasesand700Kdeaths,reportedasoftheendofJuly2020[5].AccordingtorecentsurveysfromtheCensusBureauandtheCentersforDiseaseControlandPreventionandotherstudies,theCOVID-19crisishasbeenreportedtobeassociatedwithrapidrisesinpsychologicaldistressacrossmanynations[6],withwomen,theyoung,thelesseducated,andsomeethnicminoritygroupsreportinggreatermentalhealthstrain[7].Ontheonehand,personsareworriedaboutthedirecteffectsofpotentialinfection,includingfearsofdeath,lastingdisabilities,orexacerbatingchronicillnesses.Ontheother,actionstomitigatethespreadofCOVID-19,includingsocialdistancing,quarantines,andbusinessclosureswithresultingjoblosses,areapowerfulsourceoflifedisruptionsandemotionaldistress.

FearandanxietyaboutadiseaseasinfectiousasCOVID-19cantriggernew-onsetorexacerbateexistingmentalillness[8].Therefore,thepracticalimpactofthecrisisisfargreaterthantheactualnumberofinfectioncasesorfatalities[9].Whileexpressionsofdistressmaystemfromconcernandworryrelatingtothedirectimpactsofthedisease,theymayrelateasmuchtodisruptionofregularroutines,sleepandeatingpatterns,havingout-of-schoolchildrenathomefull-time,economic

hardshipsandunusualvolatilityinfinancialmarkets,andforcedgeographicaldisplacementorconfinement.Indeed,somepeopleareatriskofdevelopingpost-traumaticdistressduetoexposuretothemulti-faceteduncertainties,orfromconfrontingdyingpersonsorlostlovedones.Whilediseasemitigatingeffortssuchas“socialdistancing”and“self-quarantining”arerecommended[10–13],individualsinmedicalisolationmayexperienceincreasedsymptomsofanxietyanddepression,aswellasfeelingsoffear,abandonment,loneliness,andstigmatization[14,15].

DespiteconcernsaboutthemyriadofsocialandbehavioralissuesassociatedwiththeCOVID-19pandemic[16,17],researchhasbeenscanttoexamineitspsychosocialimpactsorhowtopredictandmitigatethem.AlthoughitisanticipatedthatCOVID-19willhavebroadlyramifyingeffects[18,19],publichealthworkersandcrisisinterventionistsarelimitedintheirabilitytoextendservicesandsupportinatimely,preemptivefashion.Althoughsurveysareastepforwardtosupportsuchefforts[7],duetotheirretrospectiverecallbias,limitedscalability,andwithoutbeingabletoprovidereal-timeinsights,publichealthworkersarenotonlyunabletoprioritizeservicesforthemostvulnerablepopulations,butmorespecifically,lessequippedtodirectpreventioneffortstowardsindividualswithgreaterpropensitiesforadversepsychologicalimpacts.

Thispaperseekstoaddresstheabovegapbydrawinginsightsintopeople’sexpressedmentalhealthconcernsbyleveragingsocialmediadata.Theriseinonlineandsocialmediaactivityhasprovidedanunprecedentedopportunitytoenhancetheidentificationandmonitoringstrategiesofvariousmentalandpsychosocialdisorders[20,21].Over80%ofU.S.adultsusesocialmediadaily[22],placingitaheadoftexting,email,andinstantmessaging,anddiscloseconsiderablymoreaboutthemselvesonlinethanoffline[23,24].Socialmediaprovidesareal-timeplatformwherepeopleoftencandidlyself-disclosetheirconcerns,opinions,andstrugglesduringthispandemic[25].Ourresearchis,therefore,foundedonpriorworktounderstandpeople’spsychosocialdistressintermsoftheirsymptomaticmentalhealthexpressionsofanxiety,depression,stress,andsuicidalideation,andtheirexpressionsseekingemotionalandinformationalsupport[20,26–29].

Methods Data Tostudypeople’spsychosocialexpressionsonsocialmedia,weobtainTwitterdata.Twitterisoneofthemostpopularsocialmediaplatforms,anditspublic-facing,micro-bloggingbaseddesignenablespeopletocandidlyself-discloseandself-expresstheirlifeexperiencesandconcerns[30].

TreatmentData.Inparticular,wefocusourstudyontheU.S.populationandleveragetheTwitterstreamingAPI.Usinggeo-boundedcoordinates,wecollect1%ofreal-timeTwitterdataoriginatingfromtheU.S.Wecollect59,096,694TwitterpostsbetweenMarch24,2020,andMay24,2020.BecausethisdatasetcomesfromthesameperiodwhentheCOVID-19outbreakoccurred,welabelthisdatasetasthe

Treatmentdataset.WenotethatthisperiodsawanexponentialgrowthinreportedCOVID-19infectioncases(~50Kto~1M)andfatalities(~1Kto~56K)intheU.S.[31].Duringthesetwomonths,federalandstatepoliciesandlawswereenactedtocontrolormitigatethespreadoftheoutbreak,includingschoolandworkclosures,stay-at-homeorders,andCoronavirusAid,Relief,andEconomicSecurityAct[32].

ControlData.TounderstandthesocialmediaexpressionsparticularlyattributedtotheCOVID-19crisis,weobtainacontroldatasetthatoriginatesfromthesamegeographicallocation(U.S.)andsimilartimeperiod,butfromthepreviousyear(2019).Priorwork[33]motivatesthisapproachofobtainingcontroldatathatactsasabaselineandlikelyminimizesconfoundingeffectsduetogeo-temporalseasonalityinlifestyle,activities,experiences,andunrelatedeventsthatmayhavesomepsychosocialbearing.Weobtainasimilarly-sizeddatasetof40,875,185TwitterpostssharedbetweenMarch24,2019,andMay24,2019.

Psychosocial Effects of COVID-19 TounderstandthepsychosocialimpactsoftheCOVID-19outbreak,weconducttwotypesofanalysisonourTwitterdataset,whichwedescribebelow.Ourworkbuildsuponthevast,rapidlygrowingliteraturestudyingmentalhealthconcernsandpsychosocialexpressionswithinsocialmediadata[20,23,26–28,30,34–37].

Symptomatic Mental Health Expressions Drawingontheworkreferencedabove,wehypothesizethatpeople’sself-disclosureexpressionsonsocialmediacanrevealsymptomaticmentalhealthexpressionsattributedtotheCOVID-19crisis.Weexaminesymptomaticexpressionsofanxiety,depression,stress,andsuicidalideation.Thesearenotonlysomeofthemostcriticalmentalhealthconcernsbutalsohavebeenattributedtobeconsequencesofthepandemicoutbreak[16,38,39].

Toidentifymentalhealthsymptomaticexpressionsinsocialmedialanguage,Sahaetal.(2019)builtmachinelearningclassifiers[28]usingtransferlearningmethodologies---themainideahereistoinfermentalhealthattributesinanunlabeleddatabytransferringaclassifiertrainedonadifferentlabeleddataset.Theseclassifiersaren-gram(n=1,2,3)basedbinarySupportVectorMachine(SVM)modelswherethepositiveclassofthetrainingdatasetsstemsfromappropriateRedditcommunities(r/depressionfordepression,r/anxietyforanxiety,r/stressforstress,andr/SuicideWatchforsuicidalideation),andthenegativeclassoftrainingdatasetscomesfromnon-mentalhealth-relatedcontentonReddit—acollatedsampleof20Mposts,gatheredfrom20subredditsfromthelandingpageofRedditduringappropriatelythesameperiodasthementalhealthsubredditposts,suchasr/AskReddit,r/aww,r/movies,andothers.Theseclassifiersperformatahighaccuracyofapproximately0.90onaverageonheld-outtestdata[28].

ClinicalValidity.Sahaetal.’sclassifiers,usedhere,havealsobeenshowntotransferwellonTwitterwithan87%agreementbetweenmachine-predictedlabelsandexpertappraisal[28],whereexpertsannotatedpostsintheclassificationtest

datausingDSM-5[40]criteriaofmentalhealthsymptoms.Bagroyetal.[41]reportedadditionalvalidationofsuchderivedinsightswithfeedbackfromclinicalexperts.Inthiswork,theoutcomesofthementalhealthexpressionclassifierswerecomparedwiththosegivenbyhumancodersonthesame(random)sampleofsocialmediaposts;thelattercodedthepostsbasedonacodebookdevelopedusingpriorqualitativeandquantitativestudiesofmentalhealthdisclosuresonsocialmediaandliteratureinpsychologyonmarkersofmentalhealthexpressions.Codersnotonlyagreedwiththeoutcomesoftheclassifiers(Cohen’sκwas0.83),butalsonotedthattheclassifierscouldidentifyexplicitexpressionsoffirst-handexperienceofpsychologicaldistressormentalhealthconcerns(“igetoverwhelminglydepressed”)aswellasexpressionsofsupport,help,oradviceseekingarounddifficultlifechallengesandexperiences(“arethereanyresourcesIcanusetotalktosomeoneaboutdepression?”).Furtherdetailsabouttheseclassifiers,includingtheirdetailedperformance,predictivefeaturesdemonstratingmodelinterpretability,andefficacyoftransfertoTwitterdata,maybefoundin[28,33,41].WeusetheseclassifierstomachinelabelbothourTreatmentandControldatasets.

Support-seeking Expressions Socialsupportisconsideredanessentialcomponentinhelpingpeoplecopewithpsychologicaldistress[42].Researchreportsthatsupportiveinteractionscanevenhavea“bufferingeffect”[43];thatis,theycanbeprotectiveagainstthenegativeconsequencesofmentalhealth.Withthewideadoptionofwebandsocialmediatechnologies,support-seekingisincreasinglyhappeningonlineandhasbeenshowntobeefficacious[23,44].Infact,ameta-analysisindicatesthatonlinesupportiseffectiveindecreasingdepressionandincreasingself-efficacyandqualityoflife[45].Inthecontextofsuicide,certaintypesofsocialsupportinRedditcommunitiesmayreducethechancesoffuturesuicidalideationamongthoseseekingmentalhealthhelp[46].Ohetal.furthershowedthatsurveyedFacebookusersdemonstrateapositiverelationshipbetweenhavinghealthconcernsandseekinghealth-relatedsocialsupport[47].Indeed,duringglobalcrisessuchasCOVID-19,whenmanyofthephysicalsitesforhealthcare(includingmentalhealth)havebeenclosedorhaveveryrestrictedaccess,itislikelythatonlinesupporthasproliferated[48].Fearofpotentialinfectionmayfurtherhavealienatedindividualsinneedtopursueformaltreatment,therapy,andsupport,perhapschannelizingtheirsupportseekingeffortsonlineandonsocialmedia.

Accordingtothe“SocialSupportBehavioralCode”[49],twoformsofsupportthathavereceivedtheoreticalandempiricalattentionareemotionalandinformationalsupport.Emotionalsupport(ES)correspondstoempathy,encouragement,andkindness,whileinformationalsupport(IS)correspondstoinformation,guidance,andsuggestions[50,51].Thesetwoformsofsupporthavebeenfoundtobemostprevalentandeffectiveinseveralstudiesofonlinesupportandsocialmedia[46,50,52,53].Socialmediaenableindividualstoself-discloseandexpressinmakingtheiremotionalandinformationalneedsknownandsought[53].Andalibietal.foundthatthesetwokindsofsupportcanco-occurwithotherformsofsupport,suchaspostsseekingemotionalsupportoftenseekesteemandnetworksupport[52],and

Attaietal.notedthatTwitteriseffectiveinseekingandprovidinghealth-relatedinformationalneeds[54],contextuallyrelatedwithourproblemofinterest.

Toidentifysupportexpressionsonsocialmedia,weuseanexpert-appraiseddatasetandclassifierbuiltinpriorwork[50,55].ThesearebinarySVMclassifiersidentifyingthedegree(high/low)ofESandISinsocialmediaposts.Whenthepredictionsoftheseclassifierswerecross-validatedwithexpertannotationsfromSharmaandDeChoudhury’sdata[50],theclassifierswerefoundtohavek-foldcross-validationaccuraciesof0.71and0.77inESandISclassificationsrespectively[55].Similartothesymptomaticexpressionsclassifiers,theclassifiersofsupportexpressionsaretransferredfromRedditandtypicallyperformswellinourdatasetduetothehighlinguisticequivalencebetweenRedditandTwitterdatasets[35].Wefurthermanuallyinspectarandomsetof125Twitterpostsinourdatasetusingthemethodsoutlinedinpriorwork[28,41]torateeachTwitterpostwithbinaryhighorlowESandIS.Wefindthatthemanualratingsandclassifierratingsshowahighagreementof88%and93%,respectively,indicatingstatisticalsignificanttransferclassificationonTwitter.WeusetheseclassifierstolabelthepresenceofESandISinourTreatmentandControldatasets.

Examining Psychosocial Expressions over Time and Language Next,wedescribemethodstoexaminehowtheCOVID-19pandemicmayhavecausedchangesinpsychologicalexpressionsbycomparingourTreatment(outbreakyear)andControl(no-outbreakyear)datasets.Forbothourdatasets,weaggregatethenumberofpoststhatexpresssymptomaticandsupport-seekingexpressionsbydayandbytype.Wecomparethepervasivenessofeachkindofmeasureinthedatasets,alongwithconductingstatisticalsignificanceintheirdifferencesusingpairedt-tests.

Temporal Variation TocomparethedailyvariationofmeasuresbetweenTreatmentandControldatasets,wetransformourdataintostandardizedz-scores.OurdatasetsrelyontheTwitterstreamingAPI,andaresubjecttodailyinconsistenciesofavailabledataeachday[56].Transformedz-scoresarenotsensitivetosuchabsolutevaluesandinconsistencies,andessentiallyquantifythenumberofstandarddeviationsbywhichthevalueoftherawscoreisaboveorbelowthemean.Similarstandardizationtechniqueshavebeenadoptedinpriorsocialmediatime-seriesstudies[33,57].z-scoresarecalculatedas(x−μ)/σ,wherexistherawvalue,μisthemeanandσisthestandarddeviationofthepopulation.Here,toobtainpopulationμandσ,inadditiontoourTreatmentandControldata,wealsoincludeyear-longTwitterdataofover240MTwitterposts(September2018toAugust2019).Foreachofthemeasuresinsymptomaticandsupport-seekingexpressions,wecalculatethez-scoreperdayandinterpretpositivez-scoresasvaluesabovethemean,andnegativez-scoresasthosebelowthemean.

Linguistic Differences ToexamineCOVID-19relatedlinguisticdifferencesinthepsychosocialexpressionsonsocialmedia,weemployanunsupervisedlanguagemodelingtechnique,theSparseAdditiveGenerativeModel(SAGE)[58].Givenanytwodatasets,SAGEselectssalientkeywordsbycomparingtheparametersoftwologisticallyparameterized-multinomialmodelsusingaself-tunedregularizationparametertocontrolthetradeoffbetweenfrequentandrarekeywords.WeconductSAGEtoidentifydistinguishingn-grams(n=1,2,3)betweentheTreatmentandControldatasets,wheretheSAGEmagnitudeofann-gramsignalsthedegreeofits“uniqueness”orsaliency.SAGEallowsustoobtainhowtheexpressionsdifferduringtheCOVID-19outbreakascomparedtotheControlperiod.WeconducttwoSAGEanalyses,oneeachforsymptomaticexpressionsandsupport-seekingexpressions.Forthesymptomaticexpressions,wefirstobtainpoststhatareindicativeofeitherofanxiety,depression,stress,orsuicidalideationinTreatmentandControl,andobtainSAGEforthetwodatasets.Wedosimilarforsupport-seekingexpressionsbyobtainingpoststhatareindicativeofeitheremotionalorinformationalsupport.

Finally,wecross-examinethesalientkeywordsacrosssymptomaticandsupport-seekingexpressions,tostudyhowconcernsareprevalentineitherorbothofthekindsofexpressions.Wemeasurelog-likelihoodratios(LLR)alongwithadd-1smoothing,whereLLRcloseto0indicatescomparablefrequencies,LLR<1indicatesthegreaterfrequencyinsymptomaticexpressionsandLLR>1indicatesthegreaterfrequencyinsupport-seekingexpressions.Togethertheselinguisticanalysesenableustoobtainpsychologicalconcerns,andunderstandhowCOVID-19haspsychosociallyaffectedindividuals,andtocontextualizetheseconcernsintheliteratureonconsequencesofglobalcrises.

Results WesummarizeourfirstsetofresultsinTable1.Forallourmeasures,wefindstatisticalsignificance(aspert-tests)insocialmediaexpressionsintheTreatmentdataascomparedtothatinControl.Assumingthatmostotherconfounderswereminimizedduetothegeo-temporalsimilarityofthedatasets,ourfindingsindicatethattheCOVID-19outbreakledtoanincreaseinpeople’ssymptomaticandsupportexpressionsofmentalhealth.Weelaborateontheresultsbelow.

Table1.ComparingsocialmediaexpressionsinTreatment(2020)andControl(2019)(*p<0.05,**p<0.01,***p<0.001). Treatment(2020) Control(2019) Expression Mean Stdev. Mean Stdev. Δ% t-stat.

SymptomaticMentalHealthExpressionsAnxiety 1.65 0.20 1.35 0.08 21.32 12.31***Depression 9.00 0.60 8.17 0.35 10.18 10.56***Stress 19.31 0.77 18.61 0.43 3.76 3.05**SuicidalIdeation 3.14 0..31 2.62 0.13 19.73 13.46***

SupportExpressionsEmotionalSupport 8.56 0.84 8.17 0.50 4.77 2.85**InformationalSupport 1.75 0.18 1.67 0.08 4.78 3.50***

Temporal Variation Figure1showsthechangesinsymptomaticmentalhealthexpressionsforthesameperiodinTreatment(2020)andControl(2019)years.WefindthattheTreatmentandControlshowsignificantdifferencesinthepeople’ssymptomaticexpressions(Table1),amongwhich,anxietyshowsthemostsignificantincrease(21.32%),followedbysuicidalideation(19.73%),depression(10.18%),andstress(3.76%).Figure2showstheevolutionofsupport-seekingexpressionschangeintheTreatmentandControldatasets.Likeabove,thedifferencesaresignificant(Table1),andwefindthatnotonlyemotionalsupportincreasesby4.77%,andinformationalsupportalsoincreasesby4.78%.

InboththeplotsofFigure1and2,wefindageneraltrendofnegativeslope(avg.slope=-0.03)withintheTreatmentyear,whichisclosertozeroslope(avg.slope=3.19*10−4)intheControldataset.ThismaysuggestthatwithintheTreatmentyear,people’smentalhealthexpressionsgraduallyleveledoutovertime,despitethegrowingrateofCOVID-19activecases.Theplotsindicatethatpsychologicalexpressionsalmostconvergeatthetails.Thiscouldlikelybeduetopeople’shabituationwiththesituationandsurroundingswiththepassageoftime[59],ashasbeenobservedforothercrisisevents[33,60];however,thisneedstobeexploredfurther.WithintheControldataset,weobserveasuddenpeakonApril28,2019,whichcouldbeattributedtoashootingincidentatasynagogueinSanDiego[61].TheobservationsreflectthattheCOVID-19pandemichasincreasedpeople’smentalhealthexpressionsonsocialmedia,aligningwithothercontemporaryliteratureandmediareports[8,38].

Figure1.Comparisonofsymptomaticmentalhealthexpressionsonsocialmediapostsinthesameperiod(March24-May24)in2019and2020(COVID-19outbreakyear).

Figure2.Comparisonofsupportexpressionsonsocialmediapostsinthesameperiod(March24-May24)in2019and2020(COVID-19outbreakyear).

Linguistic Expressions Symptomatic Mental Health Expressions Table2summarizesthelanguagedifferencesasperSAGEforpostsexpressinghighmentalhealthexpressionsinTreatmentandControlperiods.AmajorityofthekeywordsthatoccurintheTreatmentperiodarecontextuallyrelatedtotheCOVID-19pandemic,suchascovid19,coronavirus,socialdistancing,stayathomeisolation.

Thesekeywordsareusedinpostsexpressingmentalhealthconcernseitherexplicitly,e.g.,“Socialdistancingisbothsadandanxiety-inducingatthesamemoment”,orimplicitly,e.g.,“Inordertogetmyfamilytreated,Iwilldomorethanbeg,andIwilldonate25KforresearchtodevelopCOVID19vaccine.”WealsofindthattheTreatmentperioduseskeywordsreferringtokeypersonnelsuchasdrfauci(referringtoAnthonyFauci,oneoftheleadsintheincumbentWhiteHouseCoronavirusTaskForceintheU.S.andDirectoroftheNationalInstituteofAllergyandInfectiousDiseasessince1984[62])andpoliticalfigureslikeNuryMartinezandDonaldTrump.Further,wefindkeywords,suchasessentialworkers,doctorjobs,andriskinglives,whichdescribehigh-riskworkersituations,e.g.,“Iamnotcomplainingaboutgoingtowork,rather,Iamconcernedaboutriskingmyhealthforwork.”,andcertaintreatmentsuggestionsthatevolvedduringthisperiod[63]suchasgarlic,malaria,andhydroxychloroquine,e.g.,“Ihearamandiedafteringestingamalariadrug,thoughhetookaversionofthedrugusedforfishinfection”,and“Wouldeatingenoughgarlickeepmesafefromthesix-feetawaysocialdistancingthing?”

Table2.Topsalientn-grams(n=1.2,3)forsymptomaticmentalhealthconcernsinTreatmentandControldatasets(SAGEAnalysis[58]).

SalientinTreatment(2020) SalientinControl(2019)Keyword SAGEKeyword SAGE Keyword SAGEKeyword SAGEcovid19 11.17 flattenthecurve 7.44 hospitality -2.81 tournament -1.92lordmarvelous 10.87 doctorjobs 7.32 trainee -2.78 muslim -1.90coronavirus 10.58 garlic 7.29 crimes -2.74 florida -1.90socialdistancing 9.92 hydroxychloroquine 7.28 delay -2.55 boston -1.88nurymartinez 9.66 n95masks 7.26 traffic -2.55 cashier -1.87workingcouncilwoman 9.66 masksgloves 7.26 accident -2.39 playoffs -1.86

boreddaily 8.69practicesocialdistancing 7.21

financeaccounting -2.26

salesrepresentative -1.85

stayathomeisolation 8.69physicianjobsdoctorjobs 7.13 halffinance -2.22 springfield -1.84

quarantinelife 8.62 quarantinelife 6.98 auburn -2.21 border -1.84quarantinegot 7.87 plzhelpsmall 6.96 halftechnology -2.19 barista -1.77securityguard 7.63 smalldonation 6.96 pete -2.19 israel -1.77essentialworkers 7.62 stayhomeorders 6.92 parttime -2.18 ncclick -1.76drfauci 7.56 selfquarantine 6.88 roberthalf -2.12 playoff -1.75wenttired 7.48 positivecovid19 6.79 tickets -2.08 bracket -1.75coronaviruspandemic 7.44 riskinglives 6.79 marvel -2.07 terrorist -1.65

Support-Seeking Expressions Table3liststhetopkeywordsasperSAGEforsupport-seekingpostsinTreatmentandControlperiod.Likeabove,wefindkeywordsthatexplicitlyrelatetoCOVID-19occurintheTreatmentperiod.WealsofindthattheTreatmentperiodconsistsofpoststhatseeksupportrelatedtojobandpaysuchas,losingjobs,needpay,andfurloughed,e.g.,“Manyinourcommunityhavelosttheirjobs,areunderinsuredandarestrugglingtomakeendsmeet.Providingpantries,hotmeals,hotspotsanddistancelearningopportunitiesisnowmorecriticalthanever,pleasedonate.”Ourdataalsorevealstheprevalenceofcontextuallyrelatedkeywordssuchasmasks,ppe,hoarding,stockpile,andsanitizerthataremedicallyrecommendedprevention

andcontainmentmeasuresofCOVID-19infection,e.g.,“PleasecontactmeifyouhaveanyN95maskorknowtoobtainsome.MysisterandafewfriendworkintheORandtheydonothavethesuppliestostaysafe,theyhavepatientswhohave#COVID19.TY!#HealthcareHeroes.”

Table3.Topsalientn-grams(n=1.2,3)forsupport-seekingexpressionsinTreatmentandControldatasets(SAGEAnalysis[58]).

SalientinTreatment(2020) SalientinControl(2019)Keyword SAGEKeyword SAGE Keyword SAGEKeyword SAGElord 7.93 staysafe 4.67 hospitality -2.86 cashier -1.79fauci 6.70 foodbills 4.66 duke -2.51 springfield -1.79ventilators 6.59 disinfectant 4.64 shiftsupervisor -2.24 delay -1.76quarantine 6.47 handsanitizer 3.08 tampa -2.21 baristastore -1.76securityofficer 6.11 clorox 3.03 advisor -1.95 boston -1.76n95 5.53 medicalsupplies 2.97 customerservice -1.92 counter -1.75hopestayingsafe 5.36 tryingtimes 2.89 investigation -1.89 barista -1.74ppe 5.25 riskinglives 2.87 managerretail -1.87 columbia -1.73wearingmasks 5.20 stockpile 2.86 traffic -1.87 meetingretail -1.73

uncertaintimes 5.16 fatherpassed 2.36 muslim -1.86informationalmeeting -1.73

healthcareworkers 5.01 hoarding 2.31 storemanager -1.85 stlouis -1.72furloughed 5.00 mask 2.31 tickets -1.85 marvel -1.70

asymptomatic 4.95medicalprofessionals 2.27 playoffs -1.83 marketing -1.68

peoplequarantine 4.90 losingjobs 2.27 cubs -1.82 server -1.67fightingstigma 4.82 toiletpaper 2.05 border -1.81 accident -1.64

Linguistic Comparability Finally,Table4showstheresultsofthelexicalcomparabilityanalysis,wherelog-likelihoodratios(LLRs)demarcatethetopkeywordsusedforsymptomaticmentalhealthexpressionsandsupport-seekingexpressionswithintheTreatmentdataset.Wefindthatkeywords,suchassafetyprecautions(wearmasks),healthcareandtreatment(healthcareworkers,hospitalized,beds,andicu),andlife/death(passedaway,killpeople,humanlives,anddeaths)comparablyoverlapinbothkindsofpsychologicalexpressions(LLR~0).Thesekeywordsarealsousedtoraiseawarenessandexpresssolidaritywithhealthcareandhigh-riskworkers,e.g.,“Takingallsafetyprecautionsandadheringtotheguidelinesestablishedbyourhealthcareprofessionalswillkeepussafe.”Ourlexico-psychologicalanalysesrevealthatmoreclinicallyrelevantkeywordsandsymptomsoccurfrequentlyinsymptomaticexpressions(LLR>0),e.g.,sleepscheduleandtestedpositive,whereas,sociallyrelevantandstressfulcircumstancesaremoreprevalentinsupport-seekingexpressions(LLR<0),e.g.,imsingleparent,starve,andlostjobs.

Table4.DistributionofsocialmediakeywordsacrosshighsymptomaticmentalhealthandsupportseekingexpressionswithinTreatmentperiodusingLog-

likelihoodRatios(LLR).KeywordswithLLR>0distinctlyoccurinhighsymptomaticexpressions,thosewith<0distinctlyoccurinsupport-seekingexpressions,andthose~0occurcomparablyinboth.

LLR>0 LLR~0 LLR<0Keyword LLR Keyword LLR Keyword LLR

sleepschedule 0.75 infected -0.01 imsingleparent -1lonely 0.64 wearmasks -0.01 starve -1anxiety 0.62 needhelp -0.01 meditate -1isolation 0.56 killpeople -0.01 sorryloss -0.73staysafe 0.56 needpay 0 carepeople -0.7bored 0.56 healthcareworkers 0 hardtimes -0.45testedpositive 0.52 passedaway 0 peoplesick -0.4quarantinelife 0.52 seriousness 0 helpingpeople -0.4homeschooling 0.51 humanlives 0 sorryhear -0.39tired 0.5 deaths 0 urged -0.33doctor 0.48 domesticviolence 0 newyorkers -0.29fightingstigma 0.46 comforting 0 lostjobs -0.21depression 0.45 hospitalized 0 hopefamily -0.21stuckinside 0.42 beds 0 selfish -0.21sane 0.41 icu 0.01 desperate -0.21

Discussion

Principal Results OurstudysuggeststhatsocialmediapostsduringtheCOVID-19pandemiccontainasignificantlyhigherfrequencyofsymptomaticmentalhealthandsupport-seekingexpressionsthanacomparabledatasetfromthesameperiodinthepreviousyear.Wealsofindthattheytopicallyrelatetotheongoingcrisissituation,andincludeconcernssuchas:treatment,precautionarymeasures,lossofjobs,schoolclosings,stockpilingofbasiclivelihoodnecessities,feelinglonely,bored,andtiredoftherestrictionsandconstraintsputonbytheongoingpandemic,andsoon.OurfindingssuggestthatalthoughtheCOVID-19pandemichasamplifiedmentalhealthrisksandconcerns,itmayhaveheightenedasenseofbelongingandsolidarityamongindividuals—bringingthemtogether,raisingcollectiveawareness,andencouragingthemtoprovidesupporttooneanother.Forexample,manypeoplehavebeenconsiderateabouthealthcareandessentialworkersperforminghigh-riskjobs(Instacartdeliveryworkers,Amazonwarehouseemployees,Uberdrivers),andhaveexpresseddesireandsetupopportunitiesfordonatingtothosewhohavelostjobsduringthecrisis.Mediareportshavealsoindicatedhowbenevolentneighborshavebeentendingtotheirelderlyneighborsbydeliveringtheirgroceriesandotherbasicnecessities[64].

However,mentalhealthexpertssaythatwhilethecrisisisamplifyingriskfactorsforsuicide,thecoronavirusoutbreak’seffectonindividuals’mentalandemotionalwellbeingiscomplex[65].Suicideismultifaceted,andwhileeconomiclossisariskfactor,soaredepression,isolationandfearofthefuture.Atthesametime,thecrisisispossiblycreatingasenseofbelongingforindividualsatriskforsuicideasstress

andanxietyarenormalized,andpeoplecometogethertobettersupportoneanotherduringacrisis[66,67].AsFloridanotedinarecentarticle[68]:“Thelong-termtollonmentalhealthofsocialisolation,remotework,andeconomicinsecuritycouldhaveimpactsakintopost-traumaticstressdisorder;yet,thenewfocusonmentalhealthmayreducestigmaandincreasetheavailabilityofsupportservices.”Indeed,theworldbeyondthecrisismaybeoneinwhichmentalhealthismorehonestlyrecognizedandsupported.

Interestingly,wenotethatourfindingsindicateagraduallevelingoutoftheseexpressions—bothsymptomaticandsupportive,mayreflectadeveloping‘newnormal.’InFebruary2020,itseemedunthinkablethewhite-collarworkforceofmanycountrieswouldsoonbeworkingsolelyfromhome,itseemedunthinkableairtravelwouldplummetby96%,andallmajorsportingeventswillbecalledoff.WhiletheearlydaysofCOVID-19weretaintedwithfeelingsofshock,despair,andasenseoflackofcontrol,asshowninourdata,overtime,manyareslowlyadaptingtoanewwayoflifeandcomingtotermswiththerealitythatthepandemicisnotonlyheretostayforawhile,butmightleadtoanewworldorder.Indeed,epidemiologistssurmisethatmanyifnotmostchangessurroundingtherhythmsofourdailylifearelikelytofadeovertime,justastheydidafterthe1918influenzaepidemic[68].Inotherwords,thepandemicwouldmakeusrevisitandpossiblyreformmanyofourlifestylechoicesandcivicroles,andthepersistentdiscussionofthe‘newnormal’mayhelpbringordertoourcurrentturbulence.Othershavearguedthatperhapsthecrisisisanpreludetoa‘newparadigm,’asrecentlynotedbytheWorldEconomicForum[69]:“Feelingunsettled,destabilizedandalonecanhelpusempathizewithindividualswhohavefacedsystematicexclusionslong-ignoredbysocietyevenbeforetheriseofCOVID-19–thusstimulatingurgentactiontoimprovetheircondition.”Weshouldtherefore“revelinthediscomfortofthecurrentmomenttogeneratea‘newparadigm,’nota‘newnormal.’Thelevelingouttrendinourdatagivesempiricalgroundtotheseconjectures.

Nevertheless,ifrobustanti-viraltreatmentsaredevelopedandrolledoutrelativelyquicklyand/orifavaccinebecomesavailablesoonenough,presumably,thechangeswillbeshort-lived,andthenewnormalmaybetemporary.Butifthepandemiccomesbackinlargerwavesoverthenextfewseasons,likewasthecasewithhistoricalepidemics,theeconomic,political,andsocialcrisesthathavearisenasaconsequencewillleadtodeeperramificationsinturnleadingtolonger-lastingorpermanentchanges.Futureresearchwillneedtoexplorethepersistenceofthenewnormalandtheemergenceofapossiblenewparadigmasthepandemicevolves,andthereinthementalhealthimpactsfurtheralonginthecrisis.

Comparison with Prior Work COVID-19isnotthefirstpandemic—catastrophicpandemicshavebeenoccurringatregularintervalsthroughouthumanhistory,withthe1918influenzaepidemicbeingthelastonebeforethecurrentpandemic[70].Thebackdropofthe1918pandemicwasthatithappenedjustbeforetheadventofmodernpsychiatryasascienceandaclinicalspecialty–atimewhenpsychoanalysiswasgaining

recognitionasanestablishedtreatmentwithinthemedicalcommunity[71,72].Consequently,psychiatryhashadlittleopportunitytoconsidersuchhistoricallyimportantphenomenathroughitsclinical,scientificlens,untilnow.AlthoughoutbreaksoftheZikaandEbolavirus,MERS,andSARSmanagedtodrawglobalattention,stirringupanxietyanduncertaintyinsocieties,scholarshavenotedthatparticipationofmentalhealthexpertsinpandemicpreparednesshasremainednegligible[73].Consequently,ourabilitytounderstandmentalhealthresponsesaswellasthementalhealthburdeninpandemicoutbreakshavebeenlimited[74].Forinstance,aroutinelypracticedmethodofinfectioncontrol,quarantineandsocialdistancinghavereceivedsurprisinglylittleattentioninpsychiatricliteraturesofar.BaumeisterandLeary(1995)[75]contendedthathumansneedfrequentcontacts,andcrisiseventsfurtherstimulateaneedforaffiliationandintimacy.Therefore,prolongedisolationandseparationfromfamiliesandtheircommunitycanhaveprofoundeffectsonindividualseveniftheyarenotdirectlyaffectedbythedisease[4].Inthecurrentpandemic,theadditionallayerofextensiveuseofsocialmediaandexposuretooftensensationalizedonlinenews,whileinphysicalisolation,mayaddnewcomplexitiestoimplementingemotionalepidemiologyinmanagingconcerns,fears,andmisconceptions[76],asthesetoolshavebeenarguedtobearnegativeeffectsonpsychologicalwellbeing[77,78].

Byadoptingsocialmediaasalenstounpackthesepreviouslylessunderstooddimensionsofapandemic’smentalhealtheffects,ourworkisonesteptowardsclosingsomeoftheabove-notedgaps.ThepublishedliteraturepositsthatthedistressandanxietyamongindividualsinthisCOVID-19pandemicmayincreasetheincidenceofmentaldisorders[38,39,79];datathusfarfromtheU.S.pointtoapopulationincreaseinpsychologicaldistressof10%comparedto2018data[8],atrendwhichisinlinewithourpresentresults.TheseratesmaybehigherinthoseregionsheavilyexposedtoCOVID-19oramongindividualsworkingduringthepandemic,witharecentreviewreportingover20%prevalenceofanxiety,alsoconsistentwithourfindings[8].

PriorworkfoundthatmentalhealthdiscourseonTwitterrangesacrossstigmatizing,inspirational,resource,medical,andsocialdimensionsofexpressions[80],andourstudyrevealedsimilartopicaldiversityinourdataset.Further,wedetectedthroughsocialmediamanyofthestressesassociatedwiththepandemic–e.g.,prolongedisolation,exposuretopandemic-relateddeath,lossofincome/career,increasedworkload,andlackofpertinentandaccurateinformation.TheseresultsalignwithepidemiologicalfindingsthatCOVID-19hasledelevatedmentalhealthsymptomsforindividuals:Nelsonetal.(2020)surveyedtwothousandindividualsfromU.S.,Canada,andEuropeandfoundelevatedsymptomsofanxietyanddepressioncomparedtohistoricalnorms,andobservedfactorssimilartotheconcernswedetectedregardingsymptomaticexpressionsandthoserelatedtoseekingsupport.TheyalsoreinforcethesummarydatareleasedbytheCrisisTextLine(amajorcrisishelplineintheU.S.)listingmajorconcernsofcrisissupportsoughtduringthisperiod[81]—80%conversationsmentioning“virus”,34%mentioning“anxiety”,34%feelingsolidaritywithfriendsandfamily,etc.Along

similarlines,therehavebeennumerousreportsabouttheincreasingnumberofmentalhealthcrisishelplinecallsduringthisperiod[82,83],providingfurthersupportandexternalvalidationthatoursocialmediafindingsreflectmanyofthesameelementsofdistressexpressedofflineduringthiscrisis.

Next,ourtemporalanalysespointedtoasteadydeclineinpeople’sexpressedpsychosocialconcernsduringthetwomonthstudyperiod(Figure1&2),whichconformswithsimilarfindingsinGooglesearchqueriesasstay-at-homeordersandotherCOVID-19relatedpolicychangeswereimplementedintheU.S.[84].WenotecontemporarysocialcomputingresearchstudyingvariousaspectsofthesocialmediadiscourserelatedtoCOVID-19[48,85,86].ByprovidingcomplementaryevidencetoobservationsbyMackeyetal.[85]andStokesetal.[86]onexpressed(mentalhealth)concernsduringthecrisis,ourworkfurtherunderscorestheirfindingsusingacomparable(control)dataset,reinforcingandprovidingempiricalcredibilitytotheimpressionthattheCOVID-19pandemichasindeedcausedorcontributeddirectlytothementalhealthconcernsthatwedescribe.

Limitations Wenotesomelimitationsinourwork,manyofwhichpresentexcellentdirectionsforfutureresearch.WerecognizethelackoftransparencyrelatedtotheTwitterstreamingAPI.Recentresearchhasalsoquestionedthecredibilityofthe“1%Twitterstream”aspectnotingthatactualsamplingdataissmallerthanwhatitideallyshouldhavebeen[56].Giventhesedatalimitations,wedecidedagainstconductingseveraldescriptiveandfine-grainedanalyses(suchascomparingregions),andrefrainedfrommakingclaimsbasedoncomparingabsolutenumbersofthoseimpactedbyvariousmentalhealthconcerns.Forexample,wecannotdefinebasedonourdata,whethertherewereincreasedordecreasedTwitterpostingsduringourCOVID-19studyperiodcomparedtothesamemonthsin2019.Besides,socialmediadatainherentlysuffersfrombiasesofself-selectionandrepresentation[87],andasarecentarticlebyChunaraandCook(2020)highlights,publichealthsurveillance(includingthatforCOVID-19)canaccountforseveralfactorssuchasthe“populationatrisk”inepidemiologyanddemographicdisparitiesintheuseandbehavioralexpressionsonsocialmedia[25].

Further,whilewedidhavedatabeyondMay24,2020,wedecidedtoexcludethoseinordertokeepourfocusontheeffectsonsocialmediaexpressionsduetoCOVID-19andminimizethosethatfollowedthedeathofGeorgeFloydonMay25,2020,inthelightoftheBlackLivesMatterproteststhroughouttheU.S.[88].Wealsoareawarethat,withthecontinuingnatureofthepandemic,ourconclusionsarerestrictedtothementalhealthandsupport-seekingconcernsexpressedduringafinitestudyperiod.Eventssincetheendofthestudyperiodunderscorethedynamicnatureoftheseevents,asdifferentpartsoftheU.S.areheavilyaffected,whileothersarerecoveringandsomeremainrelativelyspared.Itwillbeimportanttoextendthisworktemporarily,increasethesizeoffuturesamples,and,wheneverpossible,addgeospatialspecificitytofutureanalyses.Thelatterwillbeespeciallyimportantforpotentialsupportiveinterventionslocally,ifonehastheresourcesandtheabilityto

assemblerecurring,near-real-timelocal“snapshots”asabasisforcommunityfocusedpreventiveinterventions.

Conclusion Ourwork,likethoseofothersstudyingothermajorevents,furtherreinforcesthepotentialutilityofaccessingandanalyzingsocialmediadatainnear-real-timeto‘takethetemperature’ofcommunities.Thiswillrequireamorefocusedandrobustcollectionoflocallytargetedinformationtobuildsamplesthataresufficientlylargetoproducereliablyrepresentativedatasetstobeusefulforpublichealthinterventions.Furtherworkisnowneededtotrackmentalhealth-relatedexpressionsandthosereflectingneedsforsupportthroughoutthepandemic,whichhasseendynamicchangesassociatedwithdiseasespreadtoareasthathadbeenlessaffectedduringtheearlymonthsoftheoutbreak.ThisgeospecificresearchmayfurtherenhanceourunderstandingofthecausalconnectionsbetweenCOVID-spreadandwavesofexpresseddistressed.Havingtheabilitytopresentlocallypertinent,contemporaneousanalysesofferstheopportunityforlocalpublichealthandmentalhealthproviders,aswellaspoliticalleaders,todevelopanddeploytargetedsupportservicesinatimelyfashion.

Acknowledgments MDCwaspartlysupportedbyaCOVID-19relatedRapidResponseResearch(RAPID)grant#2027689fromtheNationalScienceFoundation.

Conflicts of Interest JTreceivesunrelatedresearchsupportfromOtsuka.

Abbreviations COVID-19:CoronavirusDisease2019API:ApplicationProgrammingInterface

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